Individual energetics scale up to community coexistence: Movement, metabolism and biodiversity dynamics in fragmented landscapes.

Unravelling the intricate mechanisms that govern community coexistence remains a daunting challenge, particularly amidst ongoing environmental change. Individual physiology and metabolism are often studied to understand the response of individual animals to environmental change. However, this perspective is currently largely lacking in community ecology. We argue that the integration of individual metabolism into community theory can offer new insights into coexistence. We present the first individual‐based metabolic community model for a terrestrial mammal community to simulate energy dynamics and home range behaviour in different environments. Using this model, we investigate how ecologically similar species coexist and maintain their energy balance under food competition. Only if individuals of different species are able to balance their incoming and outgoing energy over the long‐term will they be able to coexist. After thoroughly testing and validating the model against real‐world patterns such as of home range dynamics and field metabolic rates, we applied it as a case study to scenarios of habitat fragmentation ‐ a widely discussed topic in biodiversity research. First, comparing single‐species simulations with community simulations, we find that the effect of habitat fragmentation on populations is strongly context‐dependent. While populations of species living alone in the landscape were mostly positively affected by fragmentation, the diversity of a community of species was highest under medium fragmentation scenarios. Under medium fragmentation, energy balance and reproductive investment were also most similar among species. We therefore suggest that similarity in energy balance among species promotes coexistence. We argue that energetics should be part of community ecology theory, as the relative energetic status and reproductive investment can reveal why and under what environmental conditions coexistence is likely to occur. As a result, landscapes can potentially be protected and designed to maximize coexistence. The metabolic community model presented here can be a promising tool to investigate other scenarios of environmental change or other species communities to further disentangle global change effects and preserve biodiversity. [ABSTRACT FROM AUTHOR]